deg2rad(x) rad2deg(x)
xyz2latlon(x, y, z)
latlon2xyz(latitude, longitude)
rgeo(n = 1, latlim = c(-90, 90), lonlim = c(-180, 180),
verbose = FALSE)
rgeo2(n = 1, latlim = c(-90, 90), lonlim = c(-180, 180),
verbose = FALSE)
googleMap(latitude, longitude, position = NULL,
zoom = 12,
maptype = c("roadmap", "satellite", "terrain", "hybrid"),
mark = FALSE, radius = 0, browse = TRUE, ...)
rgeo
.'roadmap'
,
'satellite'
, 'terrain'
, and
'hybrid'
browseURL
a numeric vector
a matrix each row of which contains a latitude and a longitude value
a matrix each row of which contains the x, y, and z coordinates of a point on a unit sphere
a data frame with variables long
and lat
.
If verbose
is TRUE, then x, y, and z coordinates
are also included in the data frame.
a data frame with variables long
and lat
.
If verbose
is TRUE, then x, y, and z coordinates
are also included in the data frame.
a string containing a URL. Optionally, as a side-effect, the URL is visited in a browser
rgeo
and rgeo2
differ in the algorithms
used to generate random positions. Each assumes a
spherical globe. rgeo
uses that fact that each of
the x, y and z coordinates is uniformly distributed (but
not independent of each other). Furthermore, the angle
about the z-axis is uniformly distributed and independent
of z. This provides a straightforward way to generate
Euclidean coordinates using runif
. These are then
translated into latitude and longitude.
rgeo2
samples points in a cube by independently
sampling each coordinate. It then discards any point
outside the sphere contained in the cube and projects the
non-discarded points to the sphere. This method must
oversample to allow for the discarded points.
googleMap
deg2rad(180)
rad2deg(2*pi)
xyz2latlon(1,1,1) # point may be on sphere of any radius
xyz2latlon(0,0,0) # this produces a NaN for latitude
latlon2xyz(45,45)
rgeo(4)
# sample from a region that contains the continental US
rgeo( 4, latlim=c(25,50), lonlim=c(-65,-125) )
rgeo2(4)
Run the code above in your browser using DataLab